Automated flow based biosensor for quantification of binary organophosphates mixture in milk using artificial neural network

• First automated flow based biosensor for binary organophosphate mixtures in milk.
• Highly sensitive detection of organophosphate mixtures using genetically modified AChEs B394 and B4.
• Artificial neural network enables good validation of modeled set of OP mixtures.
• Simple, rapid and sensitive method for milk screening.

This work presents an application of automatic flow based biosensor to detect binary (chlorpyriphos-oxon (CPO) and malaoxon (MO)) organophosphate (OP) mixtures in milk, based on artificial neural network (ANN). Genetically modified acetylcholinesterase (AChE) B394 and B4 were used as a biological recognition element for sensor development. AChE binds with OPs irreversibly, creating an anionic phosphonyl species. The enzymes were coupled on screen printed electrodes (SPEs) and inserted in a flow cell connected to the potentiostat and syringe pump. In order to model the combined response of CPO and MO, a total set of 19 mixtures were prepared using ANN. The modeling was validated with an external test of 6 milk samples spiked with CPO and MO mixtures. The spiked concentrations of CPO and MO were ranged from 5 × 10−10 to 5 × 10−12 M and 1.01 × 10−10 to 9.17 × 10−11 M, respectively. These concentrations were determined using factorial designing (FD) method and the obtained and expected recovery values in milk showed good co-relation. The average % recovery yields for CPO and MO are 109.53 and 100.66, respectively.

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